docs: def set_unit_spike_features(self, unit_id, feature_name, value):
          '''This function adds a unit features data set under the given features
          name to the given unit.
  
          Parameters
          ----------
          unit_id: int
              The unit id for which the features will be set
          feature_name: str
              The name of the feature to be stored
          value
              The data associated with the given feature name. Could be many
              formats as specified by the user.
          '''
          if isinstance(unit_id, (int, np.integer)):
              if unit_id in self.get_unit_ids():
                  if unit_id not in self._unit_features.keys():
                      self._unit_features[unit_id] = {}
                  if isinstance(feature_name, str) and len(value) == len(self.get_unit_spike_train(unit_id)):
                      self._unit_features[unit_id][feature_name] = np.asarray(value)
                  else:
                      if not isinstance(feature_name, str):
                          raise ValueError("feature_name must be a string")
                      else:
                          raise ValueError("feature values should have the same length as the spike train")
              else:
                  raise ValueError(str(unit_id) + " is not a valid unit_id")
          else:
              raise ValueError(str(unit_id) + " must be an int")